they are compatible with PyTorch and there is complete documentation and usage examples available. Large-scale real-world GNN models We focus on real-world scenarios and provide distributed GNN ...

In this tutorial we will demonstrate how to structure a distributed model training application so it can be launched conveniently on multiple nodes, each with multiple GPUs using PyTorch's distributed ...

The first set is made of message-passing layers to exchange information across nodes in the graph and use this to update the nodal ... HydraGNN supports distributed computing capabilties for scalable ...

Replace TORCH with the PyTorch version and CUDA with the CUDA version which you are using. Might take some time to install. !pip install torch-scatter -f https ...

implement graph neural networks using Python and PyTorch Geometric, and apply them to solve real-world problems, along with building and training graph neural network models for node and graph ...

Researchers have discovered a critical flaw in PyTorch ... torch.distributed.rpc. The component facilitates inter-process communication between the various nodes involved in distributed training ...